Anxiety, Depression, and Their Contributing Factors among Nurses Infected with COVID-19 in Iran: A Cross-sectional Study
IRANIAN RED CRESCENT MEDICAL JOURNAL(2022)
Abstract
Background: The coronavirus disease 2019 (COVID-19) epidemic is a great challenge among healthcare workers, especially nurses, due to their more frequent and closer contact with patients. Objectives: This study aimed to evaluate anxiety, depression, and their causes among nurses with COVID-19 infection in different wards of a hospital. Methods: This cross-sectional study was carried out between February 1st to October 30th, 2020, among all nurses with COVID-19 infection in different wards of Imam Khomeini Hospital (university hospital), Tehran, Iran. The nurses were contacted by phone, and data were collected using a self-administered, valid, structured questionnaire consisting of sociodemographic characteristics and clinical symptoms. Psychological complications, including anxiety and depression levels, were assessed and their association with other sociodemographic variables was also evaluated. Results: A total of 158 nurses were entered into the study, out of which 112 (70.2%) cases were females. Among all participants, 72.8% and 42.4% of the subjects reported anxiety and depression, respectively. The frequency of moderate to severe anxiety was significantly greater in women than in men (P<0.001). The infected nurses who worked in low-risk departments experienced a greater proportion of moderate to severe depression (P=0.004). In addition, the most prevalent reason for anxiety and depression was found to be the fear of infecting family members. Conclusion: Nurses bear a significant psychological burden during the COVID-19 pandemic, markedly when they get infected and experience clinical symptoms. Therefore, the government and other staff should provide some facilities and supportive administrative work for reducing anxiety and depression and improving nurses' psychological health.
MoreTranslated text
Key words
Anxiety, COVID-19, Depression, Nurses
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined